{"id":"W4392107087","doi":"10.1111/jbg.12859","title":"Characterization of runs of homozygosity islands in American mink using whole‐genome sequencing data","year":2024,"lang":"en","type":"article","venue":"Journal of Animal Breeding and Genetics","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; University of Guelph; Dalhousie University","funders":"Nova Scotia Mink Breeders Association; Natural Sciences and Engineering Research Council of Canada; Alliance de recherche numérique du Canada; Mitacs; Department of Agriculture, Nova Scotia; Mink Veterinary Consulting and Research Service; Canada Mink Breeders Association","keywords":"Biology; Mink; Genetics; KEGG; Genome; Runs of Homozygosity; Gene; Whole genome sequencing; Population; Gene ontology; Single-nucleotide polymorphism; Gene expression","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000400312,0.0002416082,0.0003614307,0.0009633476,0.0004261553,0.000496254,0.0002475853,0.0002527259,0.001427151],"category_scores_gemma":[0.0006466318,0.0001660876,0.0006286069,0.0008944955,0.0002432271,0.0001902868,0.000464327,0.0002636696,0.000280118],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001555605,"about_ca_system_score_gemma":0.0001699925,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002374795,"about_ca_topic_score_gemma":0.00670345,"domain_scores_codex":[0.9997272,0.00002457907,0.00001960396,0.0001509749,0.0000466282,0.00003114182],"domain_scores_gemma":[0.9996013,0.0001304138,0.0001124568,0.00004911721,0.00005456257,0.0000520902],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001107237,0.00006094965,0.4949155,0.0003868821,0.00083148,0.001112632,0.001675919,0.001624982,0.4578817,0.0003840054,0.0007576352,0.03926113],"study_design_scores_gemma":[0.00001455061,0.00006896361,0.9857287,0.0000193712,0.0001953841,0.0006024054,0.0002410588,0.002102276,0.007902191,0.000155161,0.00294785,0.00002219888],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.99436,0.0002651027,0.002284293,0.00001565974,0.000005242075,0.00001653228,0.002564871,0.00006034146,0.0004280352],"genre_scores_gemma":[0.9827356,0.0001593109,0.005988048,0.00004976719,0.000009044007,0.00005802365,0.01001078,0.0001070303,0.0008823233],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002374795,"threshold_uncertainty_score":0.004774272,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0388438302818606,"score_gpt":0.2840280034716182,"score_spread":0.2451841731897575,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}